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Activity Number: 192 - Contributed Poster Presentations: Section on Statistics and the Environment
Type: Contributed
Date/Time: Monday, July 30, 2018 : 10:30 AM to 12:20 PM
Sponsor: Section on Statistics and the Environment
Abstract #330059
Title: Statistical Methods for Evaluating the Correlation Between Timeline Follow-Back Data and Daily Process Data: Results from a Randomized Controlled Trial
Author(s): Wanjun Liu*
Companies: Penn State University
Keywords: functional data; summary measure; timeline follow-back; daily process; concordance correlation coefficient

Retrospective timeline follow-back data and prospective daily process data have been frequently collected in psychology research to characterize behavioral patterns. Although previous validity studies have demonstrated high correlations between these two types of data, the conventional method adopted in these studies was based on summary measures that may lose critical information, and the Pearson's correlation coefficient that has an undesirable property. This study introduces the functional concordance correlation coefficient to address these issues and provides a new R package to implement it. We use real data collected from a randomized controlled trial to demonstrate the applications of this proposed method and compare its analytical results with those of the conventional method. The results of this real data example indicate that the correlations estimated by the conventional method tend to be higher than those estimated by the proposed method. A simulation study shows that the magnitude of overestimation associated with the conventional method is greatest when the true correlation is about the medium size.

Authors who are presenting talks have a * after their name.

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